The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is essential for simultaneously improving patient care, accuracy in diagnosis and quality in clinical research. Sponsored by the Royal Society through the Newton Mobility Grant Scheme, a half-day workshop on reconstruction schemes for MR data was held on the 17th of August 2016 to discuss new ideas from related research fields that could be useful to overcome the shortcomings of the conventional reconstruction methods that have been evaluated up to date. Participants were 21 university students, computer scientists, image analysts, engineers and physicists from institutions from 6 different countries. The discussion evolved around exploring new av...
Magnetic resonance image (MRI) is a widely used non-invasive radiation-free imaging technique that u...
Magnetic resonance imaging (MRI) is used to image parts of the body using only electromagnetic inter...
International audienceFor the last 15 years, super-resolution (SR) algorithms have successfully been...
<p>The high-fidelity reconstruction of compressed and lowresolution magnetic resonance (MR) data is ...
[EN] The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data ...
The high-fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
© 2013 Dr. Kelvin LaytonOver the last 30 years, magnetic resonance imaging (MRI) has revolutionised ...
Artificial intelligence has opened a new path of innovation in magnetic resonance (MR) image reconst...
Proton magnetic resonance techniques have become indispensable for characterising tissues non-invasi...
Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications s...
Abstract Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitorin...
Magnetic resonance image (MRI) is a widely used non-invasive radiation-free imaging technique that u...
Magnetic resonance imaging (MRI) is used to image parts of the body using only electromagnetic inter...
International audienceFor the last 15 years, super-resolution (SR) algorithms have successfully been...
<p>The high-fidelity reconstruction of compressed and lowresolution magnetic resonance (MR) data is ...
[EN] The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data ...
The high-fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
© 2013 Dr. Kelvin LaytonOver the last 30 years, magnetic resonance imaging (MRI) has revolutionised ...
Artificial intelligence has opened a new path of innovation in magnetic resonance (MR) image reconst...
Proton magnetic resonance techniques have become indispensable for characterising tissues non-invasi...
Magnetic Resonance Imaging (MRI) is a non-invasive technique that is used in clinical applications s...
Abstract Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitorin...
Magnetic resonance image (MRI) is a widely used non-invasive radiation-free imaging technique that u...
Magnetic resonance imaging (MRI) is used to image parts of the body using only electromagnetic inter...
International audienceFor the last 15 years, super-resolution (SR) algorithms have successfully been...